In the remote sensing/aerial imaging industry, imagery may be used to capture views of a geographic area in order to identify and measure objects and/or structures within the images as well as to be able to determine geographic locations of points within the image. These are generally referred to as “geo-referenced images” and come in two basic categories:
Vertical Imagery, also known as Nadir Imagery—images captured with a camera pointed vertically downward thus generally capturing the tops of structures; and,
Oblique Imagery—images captured with a camera aimed at an angle capturing the sides, as well as, tops of structures.
One of the uses for vertical imagery and oblique imagery is in the assessment of properties for tax purposes by tax assessors. In particular, counties have been requesting aerial image providers to fly the counties to obtain aerial images for assessment purposes for years. For example, Pictometry International Corp., the assignee of the present patent application, is an aerial image provider that flies the entire county, and then creates a County Image Warehouse, which is a geospatial image database containing the complete set of oblique images for that county. The county assessor would then use this image warehouse to select comparable properties and other tasks that are part of their mass appraisal effort to establish the property tax base for the town, county, or tax appraisal district.
In many cases, government regulations dictate that the images must be captured close to the start of the calendar year and that the entire assessment process must be completed by mid-Spring. Traditionally, an airplane or a drone carries one or more cameras to fly geographic areas, such as a county or city to capture vertical imagery and oblique imagery of the geographic areas. Many images can be captured during each flight resulting in very large oblique image libraries of captured images. After the images are captured during the various flight sorties, an initial process is used to determine the actual geographic boundary of the area shown in the images. Thereafter, the images are processed through multiple steps in a post-capture processing stage to color-balance the images as well as to more accurately geo-reference the images. Thereafter, the color-balanced and geo-referenced images may be quality-control checked, and then assembled into the County Image Warehouse.
Once all the flights are complete and all of the portions of the County Image Warehouse are assembled, the completed County Image warehouse is then loaded into a geospatial database of oblique imagery allowing the newly captured images to be accessed and viewed along with the older captured images as part of an online service, such as Pictometry Online.
Pictometry Online is an online service hosted by a computer system that has a geospatial database currently containing a massive inventory of oblique and vertical imagery captured by Pictometry's Capture System. The geospatial database currently contains more than 170,000,000 images and is growing significantly each year. Once the captured images are loaded into the geospatial database, the online service allows a customer to simply navigate to an area using a query and the online service retrieves an oblique image that best represents the area of interest and then displays that oblique image in a manner that allows the user to both visualize the area of interest and to measure and extract other information contained within the image. The online service also allows the user to continuously pan through the massive database of oblique images, seamlessly moving from one image to the next. Because of this capability and because the online method of delivery reduces the information technology burden to support the County Image Warehouse, many customers are now switching over to the online delivery mechanism.
The methods discussed above for capturing images, processing images and loading images into the geospatial database have been in practice for years to permit the geospatial databases to deliver the newly captured images to particular customers. Initially, the geospatial databases were delivered on a hard drive, while more recently the delivery has been made online using an online service.
In a standard geospatial database deployment, images are “ingested” into the database and their geospatial indices are calculated to enable fast searching based on geospatial coordinates. Typically, the geospatial metadata and the image pixel data for each captured image are stored in separate database tables or areas. This is done since typically the type of access to the metadata and the image pixel data are different and thus for optimization purposes the metadata and image pixel data are stored differently. The separate database tables or areas may be a part of a relational database.
In any event, as the size of the geospatial databases increase, these ingestion steps take increasing amounts of time to complete because the regeneration and optimization of the geospatial indices becomes a more time consuming task as the number of records continues to grow. As such, common practice is to complete the processing of an “image library” (an arbitrary collection of imagery, typically of a given geospatial area) and then ingest the library into the geospatial database at the same time since it becomes time and processing prohibitive to ingest individual groups of images as they come in.
The result of this standard practice is that there is an access delay present for new collections of imagery before they are included in a massive image geospatial database. This prevents customers from being able to access imagery while it is still in the processing stage. Alternatively, the new collections of imagery can be ingested into the geospatial database, but then any subsequent improvements to the image quality or image accuracy are not available unless the new collections of imagery have been re-ingested into the geospatial database. This heavy burden, both administratively and from a resource consumption standpoint, might be possible for special projects, such as post-disaster flights, but it is not repeatable on a routine basis when operating a large fleet of aircraft that are generating thousands of new projects each capture season.
The conventional method discussed above results in a one to three month delay between when the images are captured, to when the images are available to be accessed by the customer. During this time period, the captured images are going through multiple discrete steps of the processing stage in which the image quality and/or the image accuracy is being enhanced. Exemplary steps of the processing stage include color-balancing, geo-referencing, quality control checks, and assembling the captured images into image warehouses. Since the images are required to be captured close to the start of the calendar year and the entire assessment process must be completed by mid-Spring, the assessors must appraise the properties within the entire territory in a very short amount of time. In many cases, this dictates that the county must hire or maintain a larger staff than would otherwise be needed in order to process this large number of properties in a short amount of time.
As prudent managers of taxpayer funds, the counties are interested in ways to reduce the impact of the conventional methodology by increasing the amount of time that their assessors have to appraise the properties in their territory. The present disclosure is directed to a new and improved computerized methodology that is designed to provide access to the captured images in a much shorter period of time than the conventional process.